Association of Medicare Advantage Premiums With Measures of Quality and Patient Experience

Key Points Question To what extent does the quality of care offered by Medicare Advantage plans differ across vs within monthly premium levels? Findings This retrospective cross-sectional study found statistically significant but small-to-medium sized (1-3 points of 100) improvements for most clinical and patient experience quality measures with higher premiums. There was a negative association for 1 measure; in contrast, at each premium level, there was substantial variation (≥5 points) in the quality of care among Medicare Advantage plans. Meaning These findings suggest that although there were modest improvements in the mean quality of care offered by high-premium Medicare Advantage plans, plans with high quality of care are available at every premium level.

eTable 2B. Alternative model summaries to those shown in Table 2 eTable 3. Main model results for each component of the overall MA CAHPS composite This supplemental material has been provided by the authors to give readers additional information about their work.        In the analysis file of 168,750 survey respondents as defined in the Data section, there is no missing data for the enrollee level case-mix adjustors, nor for any of the other predictors in the models (e.g., contractlevel characteristics), except for HRR. There were 3,269 (1.9%) records missing HRR, 99% of which (n=3,228) were in Puerto Rico. We created a new HRR code for PR, and another for the remaining cases where HRR was missing and the enrollee was not in Puerto Rico (n=41), and therefore all respondents in the analysis file had complete data and were included in the models. There was some missingness for MOOP (Maximum Out-of-Pocket cost) and we included that as a "missing" category in analysis & tables.
The CAHPS composite has some missingness -it is missing for n=1,762 (1.0%), survey respondents who did not respond to any of the items in the composite, so they are excluded, and the models have N=166,988 (as stated in the tables). Missingness is higher for the individual items, and the composite is the mean of non-missing items. The Flu Immunization measure has missingness; it is missing for n=7,339 (4.3%) of survey respondents. These survey respondents are omitted from the Flu Immunization models resulting in an N=161,411 (as stated in the tables).

Specification of the cut-points for Premium Levels
To check whether the results we show are likely to be sensitive to the cut points we used in defining the premium levels, we constructed both a partial residual plot (eFigure 1 below) and a partial regression plot (eFigure 2 below) illustrating the relationship between the CAHPS composite and the continuous premium measure, accounting for other model covariates.
To generate the data for the partial residual plot shown in eFigure 1, we ran a linear regression modeling the CAHPS composite employing individual-level sampling weights and adjusting standard errors for clustering on plan. Fixed effects were the plan characteristic, and case-mix adjustors described in the Methods section for the CAHPS primary model, plus HRR region, but without premiums. Residuals were retained from this model and then standardized to mean of zero and standard deviation of one. We then created a scatterplot with these standardized residuals on the y-axis and the continuous specification of the monthly premium on the x-axis. Due to the large number of data points, a loess curve was fitted to facilitate visualizing the relationship.
To generate the data for the partial regression plot shown in eFigure 2 we used the same data for the vertical axis as for the partial residual plot. For the horizontal axis data, we ran a linear regression with the continuous version of monthly premium as the outcome but otherwise the same as the model used to construct the vertical axis data. Residuals again were retained and standardized. We created the partial regression plot by plotted these two sets of residuals against each other.
The partial residual plot shows that the mean residual remains close to zero at all premium levels and there is no clear pattern of residuals increasing or decreasing as premiums change. There also is no evidence of jumps in the patient experience composite residuals at different thresholds of the premium. We selected the cut points for the premium levels used in these analyses based on ease of interpretation. The cut points for the levels are $0, $60, and $120. $60 per month is about $2 per day and $120 per month is about $4 per day. The partial regression plot does not show evidence of concerning outliers or high leverage points. Results: Report other analyses donee.g., analyses of subgroups and interactions, and sensitivity analyses All other analyses are shown in eTables 4 -8 18 Discussion: Summarize key results with reference to study objectives Discussion paragraphs 1 (key objective), 2, and 3 (summary of key results) 19 Discussion: Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias.
Discussion: Limitations section. We discuss the direction of likely potential bias but do not have any way to estimate its magnitude. We do discuss the implications of bias in this direction for the interpretation of results.